Autopilot Design for the Stanford DragonFly UAV: Validation through Hardware-in-the-Loop Simulation*

We present an embedded autopilot design for the Stanford DragonFly Unmanned Aerial Vehicle (UAV) of which the digital computer in the avionics is only capable of processing sampled data and executing discrete-time control policies. We demonstrate that linear control design is not sufficient to satisfy performance requirements for specified high performance maneuvers at slow sample rates. We design a new nonlinear digital controller using an approximate feedback linearization. The sampled nonlinear dynamics for the feedback linearization is obtained using the Adams-Bashforth method, and the resulting control law is augmented with the discrete disturbance accommodation control to improve the performance and stability of the controlled system. The control law is implemented on a Hardware-in-the-Loop Simulation, which is a testbed platform that provides a faithful laboratory representation of the DragonFly UAV in flight: sensor and actuator packet delay and communication constraints in the control, are included in this testbed. We evaluate the control law using different sample rates and present our results. Keyword: UAV flight control, discrete-time control policy, approximate feedback linearization, disturbance accommodation, embedded systems.

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